// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_CXX11_TENSOR_TENSOR_IO_H
#define EIGEN_CXX11_TENSOR_TENSOR_IO_H

namespace Eigen {

namespace internal {

// Print the tensor as a 2d matrix
template<typename Tensor, int Rank>
struct TensorPrinter
{
	static void run(std::ostream& os, const Tensor& tensor)
	{
		typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
		typedef typename Tensor::Index Index;
		const Index total_size = internal::array_prod(tensor.dimensions());
		if (total_size > 0) {
			const Index first_dim = Eigen::internal::array_get<0>(tensor.dimensions());
			static const int layout = Tensor::Layout;
			Map<const Array<Scalar, Dynamic, Dynamic, layout>> matrix(
				const_cast<Scalar*>(tensor.data()), first_dim, total_size / first_dim);
			os << matrix;
		}
	}
};

// Print the tensor as a vector
template<typename Tensor>
struct TensorPrinter<Tensor, 1>
{
	static void run(std::ostream& os, const Tensor& tensor)
	{
		typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
		typedef typename Tensor::Index Index;
		const Index total_size = internal::array_prod(tensor.dimensions());
		if (total_size > 0) {
			Map<const Array<Scalar, Dynamic, 1>> array(const_cast<Scalar*>(tensor.data()), total_size);
			os << array;
		}
	}
};

// Print the tensor as a scalar
template<typename Tensor>
struct TensorPrinter<Tensor, 0>
{
	static void run(std::ostream& os, const Tensor& tensor) { os << tensor.coeff(0); }
};
}

template<typename T>
std::ostream&
operator<<(std::ostream& os, const TensorBase<T, ReadOnlyAccessors>& expr)
{
	typedef TensorEvaluator<const TensorForcedEvalOp<const T>, DefaultDevice> Evaluator;
	typedef typename Evaluator::Dimensions Dimensions;

	// Evaluate the expression if needed
	TensorForcedEvalOp<const T> eval = expr.eval();
	Evaluator tensor(eval, DefaultDevice());
	tensor.evalSubExprsIfNeeded(NULL);

	// Print the result
	static const int rank = internal::array_size<Dimensions>::value;
	internal::TensorPrinter<Evaluator, rank>::run(os, tensor);

	// Cleanup.
	tensor.cleanup();
	return os;
}

} // end namespace Eigen

#endif // EIGEN_CXX11_TENSOR_TENSOR_IO_H
